Leader of the group Machine Learning: Peter Grunwald.

Our research group focuses on how computer programs can learn from and understand data, and then make useful predictions based on it. These algorithms integrate insights from various fields, including statistics, artificial intelligence and neuroscience.  

 Machine-learning applications are increasingly part of every aspect of life, from speech recognition on cell phones to illness prediction in healthcare. One common problem is extremely polluted data, for which no single model can provide adequate explanations. At CWI we address this issue with statistical machine learning based on combining predictions from different models and experts in order to achieve reliable conclusions.

We also study how networks of neurons in the brain process information, and how modern deep-learning methods can benefit from neuroscience. We develop novel neural networks, like Deep Adaptive Spiking Neural Networks, and also theoretical models of neural learning and information processing in biology. Applications of our work range from low-energy consumption neural machine learning to neuroprosthetics, to increased insight into the question of how the brain works.


CWI participates in new NWO Perspectief programme

CWI participates in new NWO Perspectief programme

In the coming years almost a hundred researchers are going to develop innovative technologies together with industry and social organisations. That will happen in six new Perspectief programmes, which have been given the green light by NWO, Netherlands Organisation for Scientific Research, on 21 November 2017. CWI's Machine Learning group participates in the programme Efficient Deep Learning Systems.

CWI participates in new NWO Perspectief programme - Read More…


Associated Members



Current projects with external funding

  • Machine Learning at the Intrinsic Task Pace
  • Deep Spiking Vision: Better, Faster, Cheaper (DEVIS)
  • Safe Bayesian Inference: A Theory of Misspecification based on Statistical Learning (SAFEBAYES)